When you do logistic regression you have to make sense of the coefficients. These are based on the log(odds) and log(odds ratio), but, to be honest, the easiest way to make sense of these are through examples. In this StatQuest, I walk you though two Logistic Regression Examples, step-by-step, and show you exactly how the coefficients are derived and how to interpret them.

NOTE: This StatQuest assumes that you are already familiar with...
The main ideas of Logistic Regression: [ Ссылка ]
Odds and Log(odds): [ Ссылка ]
Odds Ratio and Log(odds ratio): [ Ссылка ]
Linear Regression: [ Ссылка ] and
Linear Models: [ Ссылка ]
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0:00 Awesome song and introduction
1:13 Review of Logistic Regression Concepts
2:47 Coefficients for continuous variables
10:46 Coefficients for discrete variables
17:52 Coefficients for combinations of variable types

Correction:
15:21 The left hand side of the equation should be “log(odds Obesity)” instead of “size”.

#statquest #logistic

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